Fact checking method and system utilizing social networking information

ABSTRACT

A fact checking system utilizes social networking information and analyzes and determines the factual accuracy of information and/or characterizes the information by comparing the information with source information. The social networking fact checking system automatically monitors information, processes the information, fact checks the information and/or provides a status of the information.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims the benefit of U.S. Provisional PatentApplication Ser. No. 61/946,043, filed Feb. 28, 2014, and titled “FACTCHECKING METHOD AND SYSTEM UTILIZING SOCIAL NETWORKING INFORMATION,”which is hereby incorporated by reference in its entirety for allpurposes.

FIELD OF THE INVENTION

The present invention relates to the field of information analysis. Morespecifically, the present invention relates to the field ofautomatically verifying the factual accuracy of information.

BACKGROUND OF THE INVENTION

Information is easily dispersed through the Internet, television, socialmedia and many other outlets. The accuracy of the information is oftenquestionable or even incorrect. Although there are many fact checkers,they typically suffer from efficiency issues.

SUMMARY OF THE INVENTION

A social networking fact checking system analyzes and determines thefactual accuracy of information and/or characterizes the information bycomparing the information with source information. The social networkingfact checking system automatically monitors information, processes theinformation, fact checks the information and/or provides a status of theinformation.

The social networking fact checking system provides users with factuallyaccurate information, limits the spread of misleading or incorrectinformation, provides additional revenue streams, and supports manyother advantages.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a flowchart of a method of implementing fact checkingaccording to some embodiments.

FIG. 2 illustrates a block diagram of an exemplary computing deviceconfigured to implement the fact checking method according to someembodiments.

FIG. 3 illustrates a network of devices configured to implement factchecking according to some embodiments.

FIG. 4 illustrates a flowchart of a method of implementing social factchecking according to some embodiments.

FIG. 5 illustrates a flowchart of a method of utilizing social networkcontacts for fact checking according to some embodiments.

FIG. 6 illustrates a flowchart of a method of fact checking a user forregistration according to some embodiments.

FIG. 7 illustrates a flowchart of a method of determining a validityrating based on contacts' information according to some embodiments.

FIG. 8 illustrates an exemplary web of lies according to someembodiments.

FIG. 9 illustrates an exemplary web of lies in timeline format accordingto some embodiments.

FIG. 10 illustrates a flowchart of a method of affecting a user based ona validity rating according to some embodiments.

FIG. 11 illustrates a flowchart of a method of connecting users based onsimilar content or validity rating according to some embodiments.

FIG. 12 illustrates a flowchart of a method of fact checking mappinginformation.

FIG. 13 illustrates a flowchart of a method of using an icon to indicatea validity rating or the validity of information provided by an entityaccording to some embodiments.

FIG. 14 illustrates a flowchart of a method of awarding honors for factchecking according to some embodiments.

FIG. 15 illustrates a flowchart of a method of touchscreen fact checkingaccording to some embodiments.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

A fact checking system utilizing social networking informationdetermines the factual accuracy of information by comparing theinformation with source information. Additional analysis is able to beimplemented as well such as characterizing the information.

FIG. 1 illustrates a flowchart of a method of implementing fact checkingaccording to some embodiments.

In the step 100, information is monitored. In some embodiments, allinformation or only some information (e.g., a subset less than all ofthe information) is monitored. In some embodiments, only explicitlyselected information is monitored. In some embodiments, although allinformation is monitored, only some information (e.g., informationdeemed to be fact-based) is fact checked.

The information includes, but is not limited to, broadcast information(e.g., television broadcast information, radio broadcast information),email, documents, database information, social networking/media content(tweets/Twitter®, Facebook® postings), webpages, message boards, weblogs, any computing device communication, telephonecalls/communications, audio, text, live speeches/audio, radio,television video/text/audio, VoIP calls, video chatting, videoconferencing, images, videos, and/or any other information. Theinformation is able to be in the form of phrases, segments, sentences,numbers, words, comments, values, graphics, and/or any other form.

In some embodiments, monitoring includes recording, scanning, capturing,transmitting, tracking, collecting, surveying, and/or any other type ofmonitoring. In some embodiments, monitoring includes determining if aportion of the information is able to be fact checked. For example, ifinformation has a specified structure, then it is able to be factchecked.

In some embodiments, the social networking fact checking system isimplemented without monitoring information. This is able to beimplemented in any manner. For example, while information is transmittedfrom a source, the information is also processed and fact checked sothat the fact check result is able to be presented. In some embodiments,the fact check result is embedded in the same stream as the information.In some embodiments, the fact check result is in the header of a packet.

In the step 102, the information is processed. Processing is able toinclude many aspects including, but not limited to, converting (e.g.,audio into text), formatting, parsing, determining context,transmitting, converting an image into text, analyzing andreconfiguring, and/or any other aspect that enables the information tobe fact checked. Parsing, for example, includes separating a long speechinto separate phrases that are each separately fact checked. Forexample, a speech may include 100 different facts that should beseparately fact checked. In some embodiments, the step 102 is able to beskipped if processing is not necessary (e.g., text may not need to beprocessed). In some embodiments, processing includes converting theinformation into a searchable format. In some embodiments, processingoccurs concurrently with monitoring. In some embodiments, processingincludes capturing/receiving and/or transmitting the information (e.g.,to/from the cloud).

In a specific example of processing, information is converted intosearchable information (e.g., audio is converted into searchable text),and then the searchable information is parsed into fact checkableportions (e.g., segments of the searchable text; several word phrases).

Parsing is able to be implemented in any manner including, but notlimited to, based on sentence structure (e.g., subject/verbdetermination), based on punctuation including, but not limited to, endpunctuation of each sentence (e.g., period, question mark, exclamationpoint), intermediate punctuation such as commas and semi-colons, basedon other grammatical features such as conjunctions, based on capitalletters, based on a duration of a pause between words (e.g., 2 seconds),based on duration of a pause between words by comparison (e.g., typicalpauses between words for user are 0.25 seconds and pauses betweenthoughts are 1 second)—the user's speech is able to be analyzed todetermine speech patterns such as length of pauses between words lastinga fourth of the length for pauses between thoughts or sentences, basedon a change of a speaker (e.g., speaker A is talking, then speaker Bstarts talking), based on a word count (e.g., 10 word segments), basedon speech analysis, based on a slowed down version (recording thecontent, slowing down the recorded content to determine timing breaks),based on keywords/key phrases, based on search results, and/or any othermanner. In some embodiments, processing includes, but is not limited to,calculating, computing, storing, recognition, speaker recognition,language (word, phrase, sentence, other) recognition, labeling, and/orcharacterizing.

In the step 104, the information is fact checked. Fact checking includescomparing the information to source information to determine the factualvalidity, accuracy, quality, character and/or type of the information.In some embodiments, the source information includes web pages on theInternet, one or more databases, dictionaries, encyclopedias, socialnetwork information, video, audio, any other communication, any otherdata, one or more data stores and/or any other source.

In some embodiments, the comparison is a text comparison such as astraight word for word text comparison. In some embodiments, thecomparison is a context/contextual comparison. In some embodiments, anatural language comparison is used. In some embodiments, patternmatching is utilized. In some embodiments, an intelligent comparison isimplemented to perform the fact check. In some embodiments, exact match,pattern matching, natural language, intelligence, context, and/or anycombination thereof is used for the comparison. Any method of analyzingthe source information and/or comparing the information to the sourceinformation to analyze and/or characterizing the information is able tobe implemented. An exemplary implementation of fact checking includessearching (e.g., a search engine's search), parsing the results orsearching through the results of the search, comparing the results withthe information to be checked using one or more of the comparisons(e.g., straight text, context or intelligent) and retrieving resultsbased on the comparison (e.g., if a match is found return “True”). Theresults are able to be any type including, but not limited to, binary,Boolean (True/False), text, numerical, and/or any other format. In someembodiments, determining context and/or other aspects of convertingcould be implemented in the step 104. In some embodiments, the sourcesare rated and/or weighted. For example, sources are able to be givenmore weight based on accuracy of the source, type of the source, userpreference, user selections, classification of the source, and/or anyother weighting factor. The weighting is then able to be used indetermining the fact check result. For example, if a highly weighted orrated source agrees with a comment, and a low weighted source disagreeswith the comment, the higher weighted source is used, and “valid” or asimilar result is returned. Determining a source agrees with informationis able to be implemented in any manner, for example, by comparing theinformation with the source and finding a matching result, anddetermining a source disagrees with information is when the comparisonof the information and the source does not find a match.

In the step 106, a status of the information is provided based on thefact check result. The status is provided in any manner including, butnot limited to, transmitting and/or displaying text, highlighting,underlining, color effects, a visual or audible alert or alarm, agraphical representation, and/or any other indication. The meaning ofthe status is able to be any meaning including, but not limited to,correct, incorrect, valid, true, false, invalid, opinion, hyperbole,sarcasm, hypocritical, comedy, unknown, questionable, suspicious, needmore information, questionable, misleading, deceptive, possibly, closeto the truth, and/or any other status.

The status is able to be presented in any manner, including, but notlimited to, lights, audio/sounds, highlighting, text, a text bubble, ascrolling text, color gradient, headnotes/footnotes, an iconic orgraphical representation, a video or video clip, music, other visual oraudio indicators, a projection, a hologram, a tactile indicatorincluding, but not limited to, vibrations, an olfactory indicator, aTweet, a text message (SMS, MMS), an email, a page, a phone call, asocial networking page/transmission/post/content, or any combinationthereof. For example, text is able to be highlighted or the text coloris able to change based on the validity of the text. For example, as auser types a social network message, the true statements are displayedin green, the questionable statements are displayed in yellow, and thefalse statements are displayed in red. In some embodiments, providingthe status includes transmitting and/or broadcasting the status to oneor more devices (e.g., televisions).

The status is also able to include other information including, but notlimited to, statistics, citations and/or quotes. Providing the status ofthe information is also able to include providing additional informationrelated to the fact checked information, such as an advertisement. Insome embodiments, providing includes pointing out, showing, displaying,recommending, playing, presenting, announcing, arguing, convincing,signaling, asserting, persuading, demonstrating, denoting, expressing,hinting, illustrating, implying, tagging, labeling, characterizing,and/or revealing.

In some embodiments, the fact checking system is implemented such thatresponses, validity determinations and/or status presentations areavailable in real-time or near real-time. By real-time, it is meantinstantaneously (e.g., within 1 second); whereas near real-time iswithin a few seconds (e.g., within 5 seconds). Furthermore, since themonitoring, processing, fact checking and providing status are all ableto be performed automatically without user intervention, real-time alsomeans faster than having a human perform the search and presentingresults. Depending on the implementation, in some embodiments, theindication is presented in at most 1 second, at most several seconds(e.g., at most 5 seconds), at most a minute (not real-time), at mostseveral minutes or by the end of a show. In some embodiments, the timeamount (e.g., at most 1 second) begins once a user pauses in typing,once a phrase has been communicated, once a phrase has been determined,at the end of a sentence, once an item is flagged, or another point in asequence. For example, as soon as a phrase is detected, the factchecking system checks the fact, returns a result and displays anindication based on the result in less than 1 second—clearly much fasterthan a human performing a search, analyzing the search results and thentyping a result to be displayed on a screen.

In some embodiments, an indication is displayed to compare the factcheck result with other fact check results for other users. For example,as described herein, in some embodiments, fact check implementations areable to be different for different users based on selections such asapprovals of sources and processing selections which are able to resultin different fact check results. Therefore, if User A is informed that Xinformation is determined to be “false,” an indication indicates that Xinformation was determined to be “true” for 50 other people. In someembodiments, usernames are indicated (e.g., X information was determinedto be “true” for Bob). In some embodiments, usernames and/or results areonly provided if their result is different from the user's result. Insome embodiments, the number of users whose result matches the user'sresult is indicated. In some embodiments, the indication only indicateswhat the results were for contacts (e.g., social networking contacts) ofthe user. In some embodiments, the indication is only indicated if theresults were different (e.g., true for user, but false for others). Insome embodiments, the indication includes numbers or percentages ofother fact check implementations (e.g., true for 50 users and false for500 users or 25% true and 75% false). In some embodiments, indicationsare only indicated for specific users or classes of users. For example,only results of users classified as “members of the media” areindicated. In another example, a user is able to select whose resultsare indicated. In some embodiments, only results of users with avalidity rating above a threshold are indicated.

In some embodiments, fewer or more steps are implemented. Furthermore,in some embodiments, the order of the steps is modified. In someembodiments, the steps are performed on the same device, and in someembodiments, one or more of the steps, or parts of the steps, areseparately performed and/or performed on separate devices. In someembodiments, each of the steps 100, 102, 104 and 106 occur or are ableto occur in real-time or non-real-time. Any combination of real-time andnon-real-time steps is possible such as all real-time, none real-timeand everything in between.

FIG. 2 illustrates a block diagram of an exemplary computing device 200configured to implement the fact checking method according to someembodiments. The computing device 200 is able to be used to acquire,store, compute, process, communicate and/or display informationincluding, but not limited to, text, images, videos and audio. In someexamples, the computing device 200 is able to be used to monitorinformation, process the information, fact check the information and/orprovide a status of the information. In general, a hardware structuresuitable for implementing the computing device 200 includes a networkinterface 202, a memory 204, a processor 206, I/O device(s) 208, a bus210 and a storage device 212. The choice of processor is not critical aslong as a suitable processor with sufficient speed is chosen. The memory204 is able to be any conventional computer memory known in the art. Thestorage device 212 is able to include a hard drive, CDROM, CDRW, DVD,DVDRW, flash memory card, solid state drive or any other storage device.The computing device 200 is able to include one or more networkinterfaces 202. An example of a network interface includes a networkcard connected to an Ethernet or other type of LAN. The I/O device(s)208 are able to include one or more of the following: keyboard, mouse,monitor, display, printer, modem, touchscreen, touchpad,speaker/microphone, voice input device, button interface, hand-waving,body-motion capture, touchless 3D input, joystick, remote control,brain-computer interface/direct neural interface/brain-machineinterface, camera, and other devices. In some embodiments, the hardwarestructure includes multiple processors and other hardware to performparallel processing. Fact checking application(s) 230 used to performthe monitoring, processing, fact checking and providing are likely to bestored in the storage device 212 and memory 204 and processed asapplications are typically processed. More or fewer components shown inFIG. 2 are able to be included in the computing device 200. In someembodiments, fact checking hardware 220 is included. Although thecomputing device 200 in FIG. 2 includes applications 230 and hardware220 for implementing the fact checking, the fact checking method is ableto be implemented on a computing device in hardware, firmware, softwareor any combination thereof. For example, in some embodiments, the factchecking applications 230 are programmed in a memory and executed usinga processor. In another example, in some embodiments, the fact checkinghardware 220 is programmed hardware logic including gates specificallydesigned to implement the method.

In some embodiments, the fact checking application(s) 230 includeseveral applications and/or modules. Modules include a monitoring modulefor monitoring information, a processing module for processing (e.g.,converting) information, a fact checking module for fact checkinginformation and a providing module for providing a status of theinformation. In some embodiments, modules include one or moresub-modules as well. In some embodiments, fewer or additional modulesare able to be included. In some embodiments, the applications and/orthe modules are located on different devices. For example, a deviceperforms monitoring, processing, and fact checking, but the providing isperformed on a different device, or in another example, the monitoringand processing occurs on a first device, the fact checking occurs on asecond device and the providing occurs on a third device. Anyconfiguration of where the applications/modules are located is able tobe implemented such that the fact checking system is executed.

Examples of suitable computing devices include, but are not limited to apersonal computer, a laptop computer, a computer workstation, a server,a mainframe computer, a handheld computer, a personal digital assistant,a pager, a telephone, a fax machine, a cellular/mobile telephone, asmart appliance, a gaming console, a digital camera, a digitalcamcorder, a camera phone, a smart phone/device (e.g., a Droid® or aniPhone®), a portable music player (e.g., an iPod®), a tablet (e.g., aniPad®), a video player, an e-reader (e.g., Kindle™), a DVDwriter/player, an HD (e.g., Blu-ray®) or ultra high densitywriter/player, a television, a copy machine, a scanner, a car stereo, astereo, a satellite, a DVR (e.g., TiVo®), a smart watch/jewelry, smartdevices, a home entertainment system or any other suitable computingdevice.

FIG. 3 illustrates a network of devices configured to implement factchecking according to some embodiments. The network of devices 300 isable to include any number of devices and any various devices including,but not limited to, a computing device (e.g., a tablet) 302, atelevision 304, a smart device 306 (e.g., a smart phone) and a source308 (e.g., a database) coupled through a network 310 (e.g., theInternet). The source device 308 is able to be any device containingsource information including, but not limited to, a searchable database,web pages, transcripts, statistics, historical information, or any otherinformation or device that provides information. The network 310 is ableto any network or networks including, but not limited to, the Internet,an intranet, a LAN/WAN/MAN, wireless, wired, Ethernet, satellite, acombination of networks, or any other implementation of communicating.The devices are able to communicate with each other through the network310 or directly to each other. One or more of the devices is able to bean end user device, a media organization, a company and/or anotherentity. In some embodiments, peer-to-peer sourcing is implemented. Forexample, the source of the data to be compared with is not on acentralized source but is found on peer sources.

Social

In some embodiments, social fact checking is implemented. In someembodiments, only a user's content and/or sources and/or a user'scontacts' content and/or sources are used for fact checking. The sourceinformation is able to be limited in any manner such as by generating adatabase and filling the database only with information found in theuser's contacts' content/sources. In some embodiments, the social factchecking only utilizes content that the user has access to, such thatcontent and/or sources of users of a social networking system who arenot contacts of the user are not accessible by the user and are not usedby the fact checking system. In some embodiments, source information islimited to social networking information such that the social networkinginformation is defined as content generated by or for, stored by or for,or controlled by or for a specified social networking entity (e.g.,Facebook®, Twitter®, LinkedIn®). The social network entity is able to berecognized by a reference to the entity being stored in a datastructure. For example, a database stores the names of social networkingentities, and the database is able to be referenced to determine if asource is a social networking source or not. In some embodiments, sourceinformation is limited to the social networking information that hasbeen shared by a large number of users (e.g., over 1,000) or a verylarge number of users (e.g., over 1,000,000). The social networkinginformation is able to be shared in any manner such as sharedpeer-to-peer, shared directly or indirectly between users, shared bysending a communication directly or indirectly via a social networkingsystem. For example, source information is limited to only tweets, onlytweets received by at least 100 users, only Facebook® postings that areviewed by at least 100 users, only Facebook® postings of users with 100or more contacts, only users who are “followed” by 100 or more users,and/or any other limitation or combination of limitations. In someembodiments, source information is acquired by monitoring a system suchas Twitter®. For example, microblogs (e.g., tweets) are monitored, andin real-time or non-real-time, the tweets are analyzed and incorporatedas source information. Furthering the example, the tweets are processed(e.g., parsed), fact checked and/or compared with other information, andresults and/or other information regarding the tweets are stored assource information. In some embodiments, the source information islimited to social networking information and additional sourceinformation. For example, source information is limited to socialnetworking information and other sources with a reliability rating above9 (on scale of 1 to 10). In another example, source information islimited to social networking information and specific sources such asencyclopedias and dictionaries. In some embodiments, the fact checkoccurs while the user is logged into the social networking system anduses the content accessible at that time. In some embodiments, if acontact is invited but has not accepted, his content/sources are stillused. In some embodiments, contacts are able to be separated intodifferent groups such as employers, employees or by position/level(e.g., partners and associates), and the different groups are able to beused for fact checking In some embodiments, only a user's friends'content and/or sources are used for fact checking In some embodiments,multiple fact checks are implemented based on the groups (e.g., one factchecker including friends' information and a second fact checkerincluding co-workers' information). In some embodiments, fact checkresults are sent to contacts (e.g., social network contacts) of a user.In some embodiments, fact check results are shared using socialnetworking. For example, a user fact checks an advertisement or theadvertisement is fact checked for a user, and the result is sent toand/or displayed for contacts in the social network. In someembodiments, users are able to select if they want to receive fact checkresults from contacts. In some embodiments, users are able to be limitedto contacts where they only receive fact check results but do not haveother access (e.g., no access to personal information). For example, auser watches a show which is fact checked. When misinformation isdetected, the fact check result is sent to the user and his contacts(e.g., via a tweet). In some embodiments, only certain types of factcheck results are sent to users (e.g., only lies and misinformation).The misinformation and lies are able to be determined in any manner. Forexample, misinformation is determined automatically by determining thefactual accuracy of the information, and if the information isdetermined to be factually inaccurate, then it is misinformation. Liesare able to be determined by determining information is misinformationand analyzing intent. Intent is able to be analyzed in any manner, forexample, context (e.g., additional information, a result) of a statementis analyzed to determine intent. Misinformation, lies and othercharacterizations are able to be determined using a look-up table whichclassifies and stores information as factually accurate, misinformation,lies, and/or other characterizations. In some embodiments, informationis distinguished as misinformation or lies by manual review and/orcrowdsourcing. For example, users are presented a comment includingcontext (e.g., a video clip), and the users indicate if they think it ismisinformation or an intentional lie, then based on the user selections,a result is indicated. In some embodiments, additional information issent with the result to provide context such as a clip of the originalcontent which had the misinformation or a link to the original content.In some embodiments, social information is stored/utilized in anefficient manner. For example, personal data is stored in a fastestaccess memory location, and non-personal information provided by a useron a social network is stored in a slower location. In some embodiments,information is further prioritized based on popularity, relevance, time(recent/old), and/or any other implementation.

FIG. 4 illustrates a flowchart of a method of implementing social factchecking according to some embodiments. In the step 400, information isanalyzed. Analyzing is able to include monitoring, processing, and/orother forms of analysis. In the step 402, automatic fact checking isperformed utilizing only social network information as sourceinformation. In some embodiments, the social network information is onlysocial network information from contacts of the user (or contacts ofcontacts). In some embodiments, social network information is notlimited to contacts of the user. In some embodiments, if the automaticfact checking fails to produce a result above a quality/confidencethreshold, then manual crowdsourcing fact checking is implemented togenerate a result, in the step 404. The manual crowdsourcing isimplemented by providing/sending the information to be fact checkedwhere many users are able to find the information, fact check theinformation and send a response which is used to generate a factchecking result. For example, 1000 users perform manual crowdsourcingfact checking, and 995 of the users send a response indicating theinformation is false, and the fact checking system generates a factcheck result that the information is false. The fact check result isable to be determined in any way, for example, majority rules, percentabove/below a threshold or any other way. In the step 406, the result ispresented on the user's device. In some embodiments, fewer or additionalsteps are implemented. In some embodiments, automatic fact checking andcrowdsourcing are performed in parallel. In some embodiments, anautomatic result and crowdsource result are compared, and the resultwith a higher confidence score is used. In some embodiments, bothresults including the confidence score of each are provided. Confidenceof a result is able to be determined in any manner; for example, basedon how close source information is to the information, based on thenumber of agreeing/disagreeing sources, and/or any other manner. Forexample, if 99 sources agree with a statement (e.g., have the same textas the statement) and only 1 source disagrees with the statement (e.g.,has text that indicates or means the opposite of the statement), thenthe confidence score is 99%.

In some embodiments, only sources that a user and/or a user's contacts(e.g., social network contacts) have approved/accepted/selected are usedfor fact checking Users are able to approve/accept sources in anymanner, such as clicking approve after visiting a website, or fillingout a survey, or not clicking disapprove after visiting a website wherethe site is automatically approved by visiting, approving via socialnetworking (e.g., receiving a link or site or content from a contact),by “liking” content, by sending a tweet with a hashtag or othercommunication with the source to approve, by selecting content (e.g.,from list of selectable sources), using another social media forum(e.g., items/photos pinned on Pinterest are approved by that user,videos liked on Youtube are approved by those users) or any otherimplementation. In some embodiments, a source is approved if the sourceis fact checked by the user. In some embodiments, a source is approvedif the source has been fact checked by another entity (e.g.,automatically by fact checking system), and the user has verified oraccepted the fact check results. In some embodiments, a user is able todesignate an entity which approves/disapproves of sources for the user.For example, the user selects an automated approval/disapproval systemwhich searches/crawls sources (e.g., databases, the Web), analyzes(e.g., parses) the sources, fact checks the sources, and based on theanalysis and/or fact check results, approves/disapproves of the sourcesfor the user. In some embodiments, a source is approved if the source isassociated with an organization/entity that the user has “liked” (or asimilar implementation), where associated means approved by, written by,affiliated with, or another similar meaning. In some embodiments, a siteor other source information becomes an approved source if a user uses orvisits the source. In some embodiments, a source is approved if a useruses or visits the source while signed/logged in (e.g., signed in toFacebook® or Google+®). In some embodiments, the user must be loggedinto a specific social networking system, and in some embodiments, theuser is able to be logged into any social networking system or aspecific set of social networking systems. In some embodiments, thesources are limited to a specific method of approval such as onlysources visited while logged in. In some embodiments, a source isapproved if the source is recommended to the user (e.g., by a contact)(even if the user does not visit/review the source), unless or until theuser rejects/disapproves of the source. In some embodiments, sources aresuggested to a user for a user to accept or reject based on contacts ofthe user and/or characteristics of the user (e.g., location, politicalaffiliation, job, salary, organizations, recently watched programs,sites visited). In some embodiments, the contacts are limited to n-levelcontacts (e.g., friends of friends but not friends of friends offriends). In an example, user A approved source X, and one of hiscontacts approved source Y, and another contact approved source Z. Soonly sources X, Y and Z are used for fact checking content for user A.Furthering the example, since user A's sources may be different thanuser J's sources, it is possible to have different fact checking resultsfor different users. In some embodiments, users are able to disapprovesources. In some embodiments, if there is a conflict (e.g., one userapproves of a source and a contact disapproves of the same source), thenthe choice of the user with a higher validity rating is used. In someembodiments, if there is a conflict, the selection of the contact withthe closer relationship to the user (the user being interpreted as theclosest contact) is used. In some embodiments, if there is a conflictand multiple users approve/disapprove, then the higher of the number ofapprovals versus disapprovals determines the result (e.g., 2 usersapprove Site X and 5 users disapprove Site X, then Site X is not used).In another example, if 50 contacts approve Web Page Y, and 10 contactsdisapprove Web Page Y, then Web Page Y is approved. Again, depending onthe contacts, the fact check results could be different for differentusers. Furthering the example, User A has 50 contacts that approve WebPage Y, and 10 that disapprove. However, User B has 5 contacts thatapprove Web Page Y, and 20 contacts that disapprove Web Page Y.Therefore, Web Page Y is approved for User A and disapproved for User B.In some embodiments, users are able to approve/disapprove sources inclusters, and users are able to cluster sources. In some embodiments,users are able to share/recommend sources to contacts (e.g., via asocial networking site). For example, user A says, “I've grouped thesesources; I think they are all legit,” and the contacts are able toaccept or reject some/all of the sources. In some embodiments, togenerate viral approvals/disapprovals, when a user approves ordisapproves of a source or a group of sources, the source (or referencesto the source, for example, a link to the source) and the approval ordisapproval are automatically sent to contacts of the user (or up to nthlevel contacts of the user, for example, contacts of contacts of theuser). Similarly, when contacts of a user approve/disapprove a source,the source or reference and approval/disapproval are automatically sentto the user. In some embodiments, when a user approves/disapproves of asource, the source is automatically approved/disapproved for contacts.In some embodiments, the contacts are able to modify theapproval/disapproval; for example, although the user approved a source,Contact X selects to disapprove the source, so it is not an approvedsource for Contact X. Similarly, when contacts approve/disapprove asource, the source is automatically approved/disapproved for the userunless the user modifies the approval/disapproval. In some embodiments,users are able to limit the automatic approval to nth level contacts(e.g., only 1st and 2nd level contacts but no higher level contacts). Insome embodiments, all sources or a subset of sources (e.g., all sourcesincluding social networking content generated by users while logged intoa social networking site) are approved until a user disapproves of asource (or group of sources), and then that source (or group of sources)is disapproved. In some embodiments, sources are approved based on atweet and a hashtag. For example, a user tweets a message with the nameof a source preceded by a hashtag symbol. In another example, a usertweets a message with a link to a source or a name of a source and“#fcapproval” or “#fcdisapproval” or similar terms to approve/disapprovea source. In some embodiments, sources are approved based on contentwatched (e.g., on television, YouTube), items purchased, stores/sitesshopped at, and/or other activities by the user. For example, the userwatches Program X which uses/approves sources A, B and C foranalyzing/determining content, so those sources automatically becomeapproved for the user. In some embodiments, the sources are approvedonly if the user “likes” the show or if it is determined the userwatches the show long enough and/or enough times. For example, a countertracks how long the user watches a show, and if/when the counter goesabove a threshold, the sources affiliated with/related to the show areautomatically approved. In some embodiments, sources are linked so thatif a user approves a source, any source that is linked to the source isalso approved automatically. In some embodiments, the linked sources arerequired to be related (e.g., same/similar genre, same/similarreliability rating). For example, a user approves Dictionary A which islinked to Dictionary B and Dictionary C, so Dictionaries A, B and C, allbecome approved when the user approves Dictionary A. In someembodiments, the linked sources are displayed for the user toselect/de-select (e.g., in a pop-up window). In some embodiments,approval/disapproval of sources is transmitted via color-coded ornon-color-coded messages such as tweets, text messages and/or emails. Insome embodiments, approvals/disapprovals are transmitted automaticallyto contacts of the user upon approval/disapproval. In some embodiments,when a user is about to approve/disapprove a source, an indication ofwhat others (e.g., contacts or non-contacts of the user) have selectedis presented. For example, the user visits Webpage Z, and in the bottomcorner of the browser (or elsewhere), it is displayed that Contact Jdisapproved this source. In some embodiments, all sources are acceptedexcept ones the user manually rejects. In some embodiments, sources areable to be selected by sensing a user circling/selecting icons or otherrepresentations of the sources. In some embodiments, sources areapproved by bending a flexible screen when the source is on the screen.For example, a bend is detected by detecting pressure in the screen orin another manner, and the device determines the current source beingdisplayed. In some embodiments, sources are selected based on an entity.For example, a user specifies to use Fox News's content and sources asapproved sources. In some embodiments, any content/sources that Fox Newsdisapproved is also recognized as disapproved for the user. In someembodiments, users are able to combine entities and their sources; forexample, a user selects to use Fox News content/sources and CNNcontent/sources. If there are any conflicts, such as Fox News approvingSource X and CNN disapproving Source X, the conflicts are able to behandled in any manner such as those described herein. In someembodiments, the user handles the conflicts by selectingapprove/disapprove of each conflicting item or selects a preferredentity (e.g., if conflict, prefer CNN, so CNN's selections are chosen).In some embodiments, sources are received from/by others, and thesources are filtered based on personal preferences, characteristics,and/or selections such that only sources satisfying preferences areaccepted automatically and others are rejected or placed on hold forapproval. For example, User A is a very liberal person as determinedbased on viewing and reading habits, so when User G sends three sourcesthat he thinks User A should approve, two of the three sources areclassified as liberal, so they are automatically approved for User A,and the third source is classified as conservative, so it is placed in aqueue for User A to review and approve/disapprove. In some embodiments,sources are approved by detecting a user in a specified location. Forexample, the device determines that it is at or is detected at apolitical rally. The content/sources of the politician holding the rallyare automatically approved for the user or are presented for the userfor manual approval. In some embodiments, content/sources of theopponent of the politician are automatically disapproved (unless theyhad previously been approved; for example, by detecting them as alreadyapproved by the user). In some embodiments, when a device determinesthat it is within range of another user (e.g., by facial recognition) oranother user's device (e.g., by detecting device ID or user ID), theapproved/disapproved sources and their approval/disapproval status isprovided on the device. In some embodiments, user's are able to limittheir approval/disapproval information (e.g., only contacts are able toview). In some embodiments, sources are approved by waving a device at asource. For example, RFID or another technology is used to determinewhat sources are in close proximity (e.g., user waves smart phone in alibrary, and the books become approved sources for the user). In someembodiments, in addition to or instead of accepting/rejecting sources,users are able to set/select any other option regarding fact checkingimplementations such as which content to monitor, keywords formonitoring, how content is processed, weighting schemes for sources,priorities, and/or any other fact checking implementation option.

In some embodiments, a source is approved based on the reliabilityrating of the source and the approvals/disapprovals of the source. Forexample, a source is approved if the reliability rating and theapprovals total above a threshold. In another example, a reliabilityrating is increased by 1 (or another number) if the number of approvalsis greater than the number of disapprovals, and the reliability ratingis decreased by 1 (or another number) if the number of approvals is notgreater than the number of disapprovals, and then the source is approvedif the modified reliability rating is above a threshold. In anotherexample, the reliability rating is added to the number of approvalsdivided by the number of disapprovals divided by ten or the number ofapprovals plus the number of disapprovals, and then the modifiedreliability rating is compared with a threshold, and if the modifiedreliability rating is above the threshold, then the source is approved.In another example, the reliability rating is multiplied by the numberof approvals divided by the number of disapprovals with a cap/maximumtotal (e.g., 10), and then the modified reliability rating is comparedwith a threshold, and if the modified reliability rating is above thethreshold, then the source is approved. Any calculation is able to beimplemented to utilize the reliability rating, approvals anddisapprovals to determine if a source is approved for fact checking. Insome embodiments, weights are added to the calculations; for example, auser's approval/disapproval is given extra weight. For example,reliability rating+user's approval/disapproval (+2/−2)+contacts'approvals/disapprovals (+1/−1).

In some embodiments, social networking teams/groups are able to be setup for fact checking such that each member of a team approves,disapproves, and/or rates sources for fact checking. In someembodiments, each member of a team rates/selects other options regardingfact checking as well such as monitoring criteria, processing criteriaand/or other criteria, and the selections are used to determine how tofact check information. For example, three members of a team select toparse after every pause in the monitored information of two seconds, andtwo members select to parse after every 10 seconds, so the selection ofafter every pause of two seconds is used. In some embodiments, socialnetwork groups' fact checking results are compared to determine the mostaccurate group. For example, Groups A, B and C are compared, and thegroup with the most correct results is considered to be the mostaccurate group. Furthering the example, a set of data is fact checkedusing Group A's sources, Group B's sources, and Group C's sources, andthen the fact checking results are analyzed automatically, manually orboth to determine the most accurate fact checking results. Furtheringthe example, Group A's results were 80% accurate, Group B's results were95% accurate, and Group C's results were 50% accurate, so Group B wasthe most accurate. The groups' results are able to be comparedautomatically, manually or both. For example, if groups' results matchsimilar to the automatic fact checking system results, the groups'results are determined to be accurate. In another example, a group'sresults are analyzed manually (e.g., by a group of impartialindividuals) and manually compared with an automated fact checkingsystem's results or other groups' results. Furthering the example, thesources selected/approved by a group are used to automatically factcheck content, and the results of those fact checks are manually orautomatically compared with automatic fact check implementations usingdifferent sources or other groups' implementations. In some embodiments,the groups are ranked by accuracy. In some embodiments, the mostaccurate groups' sources (e.g., top 10 groups) are made public and/orselectable by other users, and/or the most accurate groups' sources aresent via social media (e.g., tweeted or posted) to other users with anoption to accept/reject.

Rating sources includes providing a reliability rating of a source, avalidity rating of a source, fact checking a source, and/or any otherrating. For example, a user of a team rates an opinion blog as a 1 outof 10 (1 meaning very factually inaccurate), and then the opinion blogis fact checked utilizing an automatic fact checking system (ormanually) which determines the content of the opinion blog is mostlyfactually inaccurate, so the automatic fact checking system gives arating of 1 as well. In some embodiments, users of teams do not specifya rating number for a source; rather, the users of the teamsapprove/disapprove/select sources, and the team with the most accuratesources (e.g., in number and/or in accuracy) is considered to be themost accurate team. In some embodiments, “accurate” such as an accuratesource is defined as having a reliability or accuracy rating above athreshold (e.g., above 8 on a scale of 1 to 10 with 10 being the mostaccurate), and the reliability/accuracy rating is able to be based onhow accurate the information is; for example, the information is factchecked (automatically and/or manually) and based on the fact check, thereliability/accuracy rating is determined. Furthering the example, ifthe fact check returns “factually accurate” for all segments ofinformation, then the information receives a 10 for accuracy, and if thefact check returns “factually inaccurate” for all segments of theinformation, then the information receives a 0 for accuracy. In someembodiments, sources are manually analyzed to determine areliability/accuracy rating. In an example of teams with the mostaccurate sources, a team with 1 source that is fact checked by a factchecking system and determined to be a reliability rating of 10, isconsidered to be less accurate than a team with 10 sources that all havea reliability rating of 10.In other words, accuracy and breadth of thesources are taken into account to determine the team with the bestsources. In some embodiments, the sources are classified, and breadth isdetermined not just by quantity of sources but also by the numberclasses the sources fall into. For example, 100 sources in a singleclassification (e.g., sports history) are not as accurate as 100 sourcesin 10 classifications. In some embodiments, the opposite is true. Forexample, a large number sources in a single classification would ensurea fact check using those sources would be accurate, and a sourcecollection that is very broad would not necessarily help. Furthering theexample, if the fact checking system is fact checking the first team towin back to back Super Bowls, a set of sources which include a medicalencyclopedia and a french dictionary would not be better than a set ofsources that focuses on sports. In some embodiments, accuracy is givenmore weight, and in some embodiments, breadth is given more weight. Forexample, in some embodiments, a set of 100 sources with an averagereliability rating of 9 is better than a set of 1000 sources with anaverage reliability rating of 8.In some embodiments, the set of 1000sources is considered better even though the reliability rating isslightly lower, since more information may be able to be fact checkedwith the larger breadth. In some embodiments, both sets are availableand used for fact checking, and whichever one returns with a higherconfidence score is used to provide a status of the information beingfact checked.

FIG. 5 illustrates a flowchart of a method of utilizing social networkcontacts for fact checking according to some embodiments. In the step500, users approve or disapprove sources or otherfeatures/options/elements for fact checking. In the step 502, factchecking is implemented (e.g., monitoring, processing, fact checkingand/or providing a result). In some embodiments, additional or fewersteps are implemented.

In some embodiments, sources are weighted based on the number of usersthat have accepted/rejected them. For example, a dictionary that has1000 accepts and 0 rejects is rated higher than a biased site which has5 accepts and 900 rejects. In some embodiments, this is a factor used inconjunction with other weighting systems. For example, a fact check isperformed on sources to generate a reliability rating, and theaccept/reject weighting is an additional factor for determining a finalreliability rating (e.g., reliability rating+/−accept/rejectweighting=final reliability rating).

In some embodiments, users in a social network are grouped/havedifferent levels (e.g., media, business level, regular user, politician)which affects the weight of the sources. For example, a media levelsource is given a higher weight than a regular user source.

In some embodiments, the weight of the source is utilized in factchecking such that higher weighted sources have more influence on a factcheck result. For example, a calculation in determining a fact checkresult includes: determining the number of agreeing highest weightedsources which is multiplied by the highest weight value, determining thenumber of agreeing second highest weighted sources which is multipliedby the second highest weight value, and so on until determining thenumber of agreeing lowest weighted sources which is multiplied by thelowest weight value. Then, the results are combined to determine a totalvalue, and if the total value is above a threshold, then the informationbeing fact checked is determined “confirmed,” and if the total value isnot above the threshold, then the information is “unconfirmed” or“disproved.” In another, example, the weights are applied to disagreeingsources, and if the total value is above a threshold, then theinformation is “disproved,” or if the total value is not above thethreshold, then the information is “confirmed.” In yet another example,the weighted agreeing and disagreeing values are combined or subtracted,and if the result is above a threshold, then “confirmed” and if not,then “disproved.”

In some embodiments, users' sources are weighted based on “tokens” oruser validity ratings (e.g., the higher the validity rating or highernumber of tokens earned, then the higher the source weight).

In some embodiments, emails or other messages are sent to contacts withfact check result updates. For example, an email is automatically sentwhen a contact's validity rating drops below a threshold. Other forms ofcommunication are possible such as a tweet, text message, or instantmessage.

In some embodiments, people are fact checked to confirm they are whothey say they are. For example, when a person registers for a socialnetworking site, the person is verified by fact checking. A user is ableto be verified in any manner, such as: comparing the user informationwith another social networking site, comparing the user information withan online resume, using IP address location information, using pasthistory information, comparing a past photograph of the user with acurrent photograph or a video scan (e.g., using a webcam), analyzingschool information, analyzing work information, analyzing professionalorganization information, and/or analyzing housing information.

In some embodiments, when users attempt to connect (e.g., when a userasks to join a user/friend's network or when a user is asked to joinanother user's (e.g., friend) network), a question is asked. Forexample, the user asks the friend a question, and the user determines ifthe answer is correct or not, which determines if the friend is acceptedinto the network or not. In another example, the friend asks the user aquestion, and the friend determines if the answer is correct or not,which determines if the user is accepted into the network or not. Insome embodiments, for efficiency, the user asks a generic/broad questionthat is able to be applied to many users, so the user does not have togenerate specific questions for each user. For example, “what highschool did we go to?”. In some embodiments, when a user makes aninvitation to a second user, the user inputs a question for the seconduser to answer. In some embodiments, instead of or in addition to a userasking a question, the second user (or invitee) simply sends a personalmessage that informs the user that the second user is, in fact, who hesays he is. For example, the invitee accepts the invitation, and alsomakes a comment, “I remember that weird painting of the dog in your dormroom at Stanford.” Then, the user either accepts or rejects the seconduser. In some embodiments, a user is allowed to “connect” to anotheruser but with limited access until he is verified.

FIG. 6 illustrates a flowchart of a method of fact checking a user forregistration according to some embodiments. In the step 600, a userattempts to register (e.g., with a social networking site/system or asecond social networking site/system). In the step 602, the user isverified using fact checking. In the step 604, the user attempts toconnect with a friend. In the step 606, user/friend verification occurs.In some embodiments, fewer or additional steps are implemented.

In some embodiments, after a web page, tweet, and/or any other contentis fact checked, the fact check result and any identifying information(e.g., the parsed segment) is stored and used as source information, orstored in a manner that is easily retrievable for future displays ofresults. In some embodiments, the results are stored in a cache or otherquickly accessible location. In some embodiments, the results are storedin a script (e.g., javascript) with the web page or coded in the webpage, or another implementation.

Validity Rating and Web

In some embodiments, an entity including, but not limited to, a speaker,author, user, or another entity (e.g., corporation) has a validityrating that is included with the distribution of information fromhim/it. The validity rating is able to be based on fact checking resultsof comments made by an entity or any other information. For example, ifa person has a web page, and 100% of the web page is factually accurate,then the user is given a 10 (on a scale of 1 to 10) for a validityrating. In another example, a user tweets often, and half of the tweetsare factually accurate and half are inaccurate, the user is given a5.The validity rating is able to be calculated in any manner. Inaddition to fact checking information by an entity, items such ascontroversies, bias, and/or any other relevant information is able to beused in calculating a validity rating. The severity of the informationor misinformation is also able to be factored in when rating a person orentity. Additionally, the subject of the information or misinformationis also able to be taken into account in terms of severity. In someembodiments, an independent agency calculates a validity rating and/ordetermines what is major and what is minor. In some embodiments,individual users are able to indicate what is important to them and whatis not. In some embodiments, another implementation of determining whatis major, minor and in between is implemented. The context of thesituation/statement is also able to be taken into account. In someembodiments, entities are able to improve their validity rating if theyapologize for or correct a mistake, although measures are able to betaken to prevent abuses of apologies. In some embodiments, in additionto or instead of a validity rating, an entity is able to include anotherrating, including, but not limited to, a comedic rating or a politicalrating. In some embodiments, an entity includes a classificationincluding, but not limited to, political, comedy or opinion. Examples ofinformation or statistics presented when an entity appears include, butare not limited to the number of lies, misstatements, truthfulstatements, hypocritical statements or actions, questionable statements,spin, and/or any other characterizations.

FIG. 7 illustrates a flowchart of a method of determining a validityrating based on contacts' information according to some embodiments. Inthe step 700, a user's validity rating is determined or acquired. In thestep 702, the user's contacts' validity ratings are determined oracquired. In the step 704, a complete user's validity rating isdetermined based on the user's validity rating and the contacts'validity ratings. In some embodiments, additional or fewer steps areimplemented and/or the order of the steps is modified. For example, thesteps are continuously ongoing such that if anything changes in eitherthe user's validity rating or the contacts' validity ratings, then newratings, including a new complete validity rating, are computed.

In some embodiments, relationship information is utilized in factchecking. For example, if a user's contacts have low entity/validityratings, then that information negatively affects the user's entityrating. For example, a user's base validity rating is a 7 out of 10based on fact checking results of the user's comments. Based on socialnetworking relationships, the user has 4 friends/contacts with 1 degreeof separation from the user, and each of those friends has a 2 out of 10validity rating. If the user's validity rating is calculated as FinalValidity Rating=(Base Validity Rating*10+Average Friend ValidityRating*5)/15, then the Final Validity Rating=(7*10+2*5)/15=5.3.Inanother example, the user's validity rating is calculated as FinalValidity Rating=(Base Validity Rating*10+Average Friend ValidityRating*# of friends)/(# of friends+10), then the Final ValidityRating=(7*10+2*4)/(4+10)=5.6.In some embodiments, contacts withadditional degrees of separation are utilized in determining the user'svalidity rating. In some embodiments, the additional degrees ofseparation are weighted less, and the weighting decreases as the degreeof separation increases. For example, a user's validity rating is 7, 4friends have validity ratings of 2, and 2 friends of friends havevalidity ratings of 6.If the user's validity rating is calculated asFinal Validity Rating=(Base Validity Rating*10+Average Friend ValidityRating*5+Average Second Degree Friend Validity Rating*2)/17, then theFinal Validity Rating=(7*10+2*5+6*2)/17=5.4.

In some embodiments, a web of lies/misinformation/other characterizationis generated. A web is able to be generated by fact checking informationand determining the relationship of who said what and when. Onceinformation is determined to be misleading, analysis is performed todetermine who provided the information, and then analysis is determinedif anyone provided the information before, and relationships aredetermined based on the time/date of the information and/or if there isany connection between those providing the information. For example, theweb of misinformation includes a graphic of who spreads misinformation.Each point in the web is able to be an entity or information. Forexample, a set of Republicans who made the same lie are included in thering with the misinformation shown in the middle. In another example,the web is a timeline version where the web shows who first said thelie, and then who repeated it. In some embodiments, times/dates of whenthe misinformation was said or passed on is indicated. In someembodiments, the first person to say the lie is given more negativeweight (e.g., for validity rating) as they are the origin of the lie. Inanother example, a tree structure is used to display the connections oflies. Although specific examples have been provided, there are manydifferent ways of storing the information and showing who provided theinformation. The web is able to be displayed for viewers to see who saysthe same information or agrees with a person. The web is shown when themisinformation is detected or when one of the people in the web isdetected. For example, commentator X provided misinformation, and 5people also provided the same misinformation. When commentator X isdetected (e.g., voice or facial recognition), a graphic is presentedshowing the 5 additional people who provided the same misinformation ascommentator X.

FIG. 8 illustrates an exemplary web of lies according to someembodiments. In the web shown, a first level provider 800 ofmisinformation is shown in the middle of the web. Second level 802 andthird level 804 misinformation providers are also shown further out inthe web.

FIG. 9 illustrates an exemplary web of lies in timeline format accordingto some embodiments. In the timeline format of the web, a first provider900 of misinformation is shown, followed by a second provider 902, thirdprovider 904, fourth provider 906, and fifth provider 908.

The web is also able to be used to generate relationships betweenentities. For example, user A says, “global warming is a hoax.” Then,users who have made a similar or the same comment (e.g., on theirFacebook® page, personal website, on a message board, in a tweet) arerecommended to connect/join in a social network. Same or similar phrasesare detected in any manner such as word/keyword comparison, and then amessage or any communication is sent to users that have provided thesame/similar phrase. Furthering the example, a popup is displayed on theuser's social network page that provides a list of users who have madethe same or a similar comment, and the user is asked if he wants toinvite the other users to join his network or to join their networks. Insome embodiments, a message/tweet is sent to both asking if they want to“connect.” In some embodiments, when misinformation is detected in aperson's comment, a message is sent to users in network saying thisperson said that and the fact check result shows it to be wrong.

In some embodiments, entity/validity ratings are based on relationshipswith other entities (including the web described above). Therelationships are able to be based on same cable network or samecompany. Using the web above, for example, if entities say the samemisinformation, they become linked together or connected and theirratings become related or merged.

In some embodiments, a user whose validity rating is below a lowerthreshold is automatically de-friended/disconnected/de-linked. In someembodiments, others are prompted with a question if they would like todisconnect from the user whose validity rating is below a lowerthreshold. In some embodiments, the user with a low validity rating isput in “time out” or his status remains a friend but a non-full friendstatus. For example, although the user with the low validity rating isconnected, he is not able to comment on a connected user's page. Inanother example, the capabilities of the user are limited on a socialnetworking site if his validity rating drops below threshold.

FIG. 10 illustrates a flowchart of a method of affecting a user based ona validity rating according to some embodiments. In the step 1000, avalidity rating of a user is determined to be below a threshold. In thestep 1002, the user is affected; for example, the user's access to webpages (e.g., social network) is restricted. In some embodiments,additional or fewer steps are implemented.

In another example, related to the web of lies, people are grouped(e.g., become contacts) if they send/say the same misinformation (maynot even know each other, but if they say “global warming is a hoax,”they join the same contacts as others who said same thing). In someembodiments, people who use the same phrase or quote (not necessarilymisinformation) become friends or are asked if they would like to becomefriends as someone who said the same thing. In some embodiments, userswith the same or similar validity rating are connected or asked if theywould like to connect.

FIG. 11 illustrates a flowchart of a method of connecting users based onsimilar content and/or validity rating according to some embodiments. Inthe step 1100, information is compared to determine a match. Forexample, user comments are compared to determine if they have said thesame thing such as “49ers rule!”. In some embodiments, onlymisinformation or other negative characteristic comments are compared.For example, a database stores comments that have been fact checked anddeemed inaccurate as well as the user that made the comment. Then, thosecomments are compared to determine if there are any matches betweenusers. In some embodiments, user validity ratings are compared as well.In some embodiments, users are grouped by validity rating (e.g.,validity rating is stored in a database and sortable by validityrating). In some embodiments, the validity ratings are exactly matched(e.g., all users with a validity rating of 7.0 are matched), and in someembodiments, ranges of validity ratings are matched (e.g., all userswith a 7.0 to 7.5 are matched). In some embodiments, opposite commentsare searched for. For example, a comment that says “raising taxes hurtsthe economy” and an opposite comment of “raising taxes helps theeconomy.” These comments are able to be considered an opposite match,which can then be used to join people with opposing views. In the step1102, users with matching comments and/or validity ratings are“connected” or asked if they would like to “connect” (e.g., join eachothers social network). In some embodiments, the steps occur inreal-time; for example, immediately after the user tweets, “49ersrule!,” connection suggestions are presented based on the implementationdescribed herein. Additional information is able to be provided to theusers such as the matching comment, the validity rating of the otheruser, and/or any other information. In some embodiments, additional orfewer steps are able to be implemented.

Additional Implementations

In some embodiments, mapping information is fact checked. For example, acamera device (e.g., augmented reality camera or vehicle camera) is usedto confirm traffic information on a map. Furthering the example, if amap indicates that traffic is going “fast” (e.g., over 50 mph), yet avehicle camera indicates the traffic is stopped, then an alertindicating the fact check result of “bad traffic information” is able tobe presented. In another example, if a map indicates the traffic acertain way, but a user's GPS (e.g., stand alone device or smart phoneGPS) indicates traffic differently, then an alert is provided to otherusers. In another example, accident information is fact checked bycomparing news information and/or police reports. In some embodiments,based on the fact check result, a corrected route is provided. Forexample, after fact checking a route, it is determined the traffic isnot bad for a particular road that was supposedly bad, so the route nowincludes that road. Fact checking of the mapping information is able tooccur periodically, when new information becomes available, or at anyother time. In some embodiments, mapping information from differentsources is compared. For example, G Maps indicates that traffic isflowing at 65 mph; however, A Maps shows that traffic is only going 35mph. The information from each source is compared (e.g., determine anydifferences), and analysis is performed to determine which is moreaccurate. For example, verification of either is searched for usingdirect knowledge (e.g., using vehicle camera or a camera positioned onthe side of the road or elsewhere to view traffic). Or a newsorganization is contacted for additional information. In someembodiments, the mapping information and fact checking results areshared among contacts in a social network. In some embodiments, themapping information is fact checked using social networking sourceinformation (e.g., information from contacts). In some embodiments,flying devices (e.g., drones) are utilized to provide information forfact checking. For example, the drones take images and/or videos oftraffic conditions and provide the images and/or videos as sourceinformation for comparison. In some embodiments, when an accident orother traffic issue occurs, a drone is able to be automatically directedto verify the issue by flying over to the area and acquiringinformation. For example, a user texts that an accident has occurred onInterstate X. The drone automatically receives/retrieves thisinformation, and flies into position to take pictures of the locationincluding traffic analysis. In another example, a device (e.g., a user'smobile device or a vehicle device) determines that user's vehicle ismoving much slower than the speed limit, so the device automaticallycommunicates with a drone (either directly or through a server), and thedrone utilizes GPS information of the vehicle to move into position toanalyze the traffic issues. The information acquired by the drone isthen dispersed to be used as source information. In some embodiments, aserver automatically determines the nearest drone to the position of theuser device, and directs only that drone to move to acquire information.

FIG. 12 illustrates a flowchart of a method of fact checking mappinginformation. In the step 1200, mapping information is analyzed (e.g.,monitored and processed). In the step 1202, the mapping information isfact checked. In the step 1204, a fact check result is presented. Insome embodiments, fewer or additional steps are implemented.

In some embodiments, an icon changes from a happy face to a sad face asmisinformation is given by an entity. In some embodiments, an image of aperson is changed from smiling to sad/angry. The fact checking systemcollects 2 to 5 different images of the person by detecting the person(e.g., facial recognition). Then, the system searches/crawls the web forpictures of the person using templates of smile, frown, angry face,tears, tense, stoic, neutral to do the searching. The appropriatepictures are retrieved and stored. The appropriate image is displayedwhen the misinformation calculation result is in range. For example,when zero misinformation is detected, a smiling face is displayed, andwhen 3-6 misinformation comments are detected the face displayed is afrowning face, and above 6 is a crying face. In some embodiments, tearsor other items are added to an image if the image cannot be found. Forexample, a sad image cannot be found, so tears are added to a neutralimage that was found.

FIG. 13 illustrates a flowchart of a method of using an icon to indicatea validity rating or the validity of information provided by an entityaccording to some embodiments. In the step 1300, one or more images ofan entity are acquired. In the step 1302, the entity's validity ratingis determine or the validity of the entity's comments is analyzed. Inthe step 1304, as the entity's validity rating changes or the validityof the entity's comments are analyzed, the image presented changes. Insome embodiments, additional or fewer steps are implemented.

In some embodiments, medallions/medals, tokens, ranks, points, and/orother awards/honors are provided based on user fact checking actions.For example, a user is awarded a different token for providing anaccurate fact check result for different items. Furthering the example,a user receives a “donkey” token for fact checking an item from a memberof the Democratic party, and an “elephant” token for fact checking anitem from a member of the Republican party. In some embodiments, theitem has to be an item not previously accurately fact checked (forexample, a comment by the President previously not fact checked). Insome embodiments, the fact check result is verified automatically,manually or a combination of both. In some embodiments, the userprovides the fact checked comment or identification information of thecomment as well as support for the fact check result (e.g., a websiteconfirming or disproving the comment). In some embodiments, the usermust perform a specified number of fact checks before receiving a token(e.g., 5 fact checks of Democrats to receive a “donkey” token).Additional tokens are able to include, but are not limited to: a“donk-phant” for fact checking both Democrats and Republicans, a “prez”token for fact checking the President, a “sen” token for fact checking amember of the Senate, a “house” token for fact checking a member of theHouse of Representatives, and a “news” token for fact checking anewscaster. In some embodiments, there are different levels of tokens.For example, one level of tokens is for actually fact checking, and asecond level is for merely flagging content as false, questionable, oranother characterization, and when the content is fact checked, a useris rewarded for being accurate. For example, if a user flags a commentas questionable, and then the comment is proven to be false, the user isawarded one point towards five points to obtain a second-level token. Insome embodiments, a user is penalized (e.g., points lost or demoted) forincorrectly flagging an item and/or providing an incorrect fact checkresult.

FIG. 14 illustrates a flowchart of a method of awarding honors for factchecking according to some embodiments. In the step 1400, a user factchecks or causes (e.g., flags) information to be fact checked. In thestep 1402, the user fact check or flag is analyzed/verified. In the step1404, the user is rewarded for a valid fact check. In some embodiments,fewer or additional steps are implemented.

In some embodiments, as a user acquires tokens, his label/title changes.For example, the user begins as a level 1 fact checker and is able toincrease to reach a level 10 fact checker if he acquires all of thepossible tokens. In some embodiments, users are able to specify the typeof label/title they receive. For example, users are able to specify“middle ages” which begins the user as a “peon” and goes up to “king.”Other examples include, but are not limited to: Star Wars (ewok to jediknight or storm trooper to sith lord (good/evil)), police (recruit tochief), military (cadet to captain), political (mayor to president). Byenabling the user to specify the set of labels or titles, additionalenjoyment occurs for the user. In some embodiments, a set of labels ortitles is generated for a group (e.g., social network group). Forexample, user X generates a football-labeled fact checking group whichstarts users as “punters” with the goal of becoming a “quarterback.”

In some embodiments, the label/title is based on the tokens, validityrating and/or other fact checking. A user's label/title is able to moveup or down based on the acquired tokens, validity rating and/or otherfact checking. For example, if a user acquires several tokens, but thenprovides misinformation several times, a token is able to be taken away.In some embodiments, users are provided additional features or benefitsfor a higher label/title. For example, a user with a level 8 factchecker label is provided contact information of several members of thenews media, whereas a level 1 fact checker is not provided thisinformation. Other benefits, awards and/or rewards are able to beprovided, such as monetary or item prizes. In some embodiments, thelabel/title is able to be used as a filtering tool for searches (e.g.,employee searches by employers). For example, an employer is able tosearch for candidates with “computer engineering skills” and “at leastlevel 5 fact checker.”

In some embodiments, users are rewarded for providing factually accurateinformation. For example, if a user tweets 100 times (and each of thetweets if fact checked by a fact checking system), the user receives areward such as a token or any other reward. In some embodiments, theinformation fact checked has to meet a specified criteria to qualify forcounting toward the reward. For example, the user is not able to tweet awell known fact 100 times and receive a reward. In some embodiments,steps to prevent cheating are implemented (e.g., monitoring forredundancy). In some embodiments, the information provided by the userhas to be directed to a specific topic (e.g., politics). In someembodiments, the information provided by the user needs to include akeyword to be fact checked to receive a reward. In some embodiments,only information with a specific label (e.g., hashtag) is fact checkedand count towards a reward.

In some embodiments, fact check swarms are able to be implemented. Usingsocial media (e.g., Twitter®), one or more users are able to encourageand/or trigger a fact check swarm such that many users attempt to factcheck information (e.g., a speech). Those that participate in the factcheck swarm are able to be recognized, awarded a prize, or providedanother benefit. For example, a user sends a tweet with a specifichashtag and/or other information regarding information to fact checkswarm. The users who receive the tweet are then able to participate inthe fact check swarm by researching elements of the information andproviding fact check results related to the information (e.g., bytweeting a snippet, a fact check result, and a cite to source(s) for theresult). The users in the swarm are then able to agree or disagree withthe result. If enough (e.g., above a threshold) users agree with theresult, the result is accepted and presented (e.g., tweeted or displayedon a television) to users outside of the social network.

FIG. 15 illustrates a flowchart of a method of touchscreen fact checkingaccording to some embodiments. In the step 1500, information ismonitored. In the step 1502, the information is processed. In the step1504, the information is fact checked, after detecting a touch of thetouchscreen (or a button or other implementation). In the step 1506, afact check result is provided. In some embodiments, additional or fewersteps are implemented.

In some embodiments, a touchscreen input is utilized for fact checkingWhen a user wants to flag content (e.g., a commentator talking) toindicate the information is questionable and/or to receive a fact checkresult, the user taps the touchscreen, and the last n seconds of contentare used for fact checking. For example, the content is continuouslymonitored and processed, and the fact checking system is able toretrieve previously processed information to perform the fact check.Furthering the example, a commentator is talking in a video, a user tapsthe screen, and the previous 10 seconds of content are fact checked. Insome embodiments, an additional time (e.g., 5 seconds) is fact checked.In some embodiments, the fact checking system determines the currentsegment. For example, the commentator says, “this project is a mess, itis $5B over budget.” The user taps the screen at “$5B” in the video. Thefact checking system had determined or determines that the currentsegment is “it is $5B over budget,” so that segment is fact checked. Insome embodiments, the current segment or a previous segment (e.g., toallow a delay of the user thinking) is fact checked. In someembodiments, the user is able to highlight closed caption content forfact checking. In some embodiments, when a user taps the touchscreen, alist of recent/current segments is displayed (e.g., pops up), and theuser is able to select one or more of the segments by tapping again. Insome embodiments, the list is displayed on a second or third screen. Insome embodiments, the list is based on time (e.g., most recent) and/orpriority (e.g., most relevant). In some embodiments, content ismonitored and processed, but the content is only fact checked when auser touches the touchscreen (or utilizes any other input mechanism). Insome embodiments, the user is able to use the touchscreen to select orhighlight text, information or a communication to have thattext/information/communication fact checked. For example, a user taps atweet on a screen to have the tweet fact checked. In another example, auser highlights text on a social networking page to have the text factchecked.

In some embodiments, content feeds are modified based on fact checking.Content feeds are fact checked, and a content feed with the highestfactual accuracy rating is presented on top/first. Factual accuracy andtime/date information are able to be combined for ranking/orderingcontent feeds.

In some embodiments, fact checking results are presented one after theother or in chronological order as a news/activity feed (and presentedvia social media/networking).

In some embodiments, fact checking information is displayed on a pagemostly (e.g., 95% or more) hidden behind the main content. The user canthen click on the page to view the fact check information.

In some embodiments, what time the misinformation was said is includedin timeline format or another format.

In some embodiments, misinformation is turned into jokes automaticallyto send to friends. In some embodiments, misinformation is turned into apostcard or greeting card. The misinformation is turned into a jokeand/or card by including the misinformation with a matching image and/ortemplate. The match is able to be made using a keyword or any othermanner. For example, if the misinformation is from Politician Z, acaricature of Politician Z is included as well as the misinformation andthe fact check result or a correction of the misinformation. In someembodiments, additional text, audio, images and/or video is providedsuch as an “oops!” sound or text, or silly music or any other effect toadd humor.

In some embodiments, the sources are rated using a rating system so thatsources that provide false or inaccurate information are rated as pooror unreliable and/or are not used, and sources that rarely providemisinformation are rated as reliable and are used and/or given moreweight than others. For example, if a source's rating falls or is belowa threshold, that source is not used in fact checking. In someembodiments, users are able to designate the threshold.

In some embodiments, comments are classified (e.g., high/false,mid/misleading, low/unsupported), and users are able to select whichclassification of information to exclude or receive. In someembodiments, “high” excludes only false information, “mid” excludesfalse and misleading information, and “low” excludes false, misleadingand unsupported information. In an example, user A accepts allinformation, but user B excludes only false information. Wheninformation is excluded, it is muted, crossed out, blacked out, notprovided, deleted, not transmitted and/or any other exclusion.

In some embodiments, fact check results are displayed when a user visitsa page (or views other content such as a video or a television show)based on previous fact checks done by/for other users. For example, UserA visits Webpage X, and a selectable/clickable link appears for the userto see the fact check result that was done by the fact check system forContact B of that page. In some embodiments, only fact checks performedby/for contacts of the user are displayed. In some embodiments, factchecks performed by/for anyone are displayed. In some embodiments, onlymanual fact checks are displayed, only automatic fact checks aredisplayed (e.g., automatically performed by the fact checking system) oronly automatic fact checks that have been manually reviewed aredisplayed. In some embodiments, the user is able to select to have afact check performed by the fact checking system using the user'ssources and compare the results with the previously performed factcheck(s). In some embodiments, only differences between the fact checkresults are displayed. In some embodiments, sources/criteria for theuser's fact check implementation is automatically compared with aprevious fact check's sources/criteria, and the user's fact check isonly performed if the user's fact check sources/criteria is different(e.g., substantially different) from the previous fact check'ssources/criteria. Substantially different is able to be determined basedon the number of different sources (e.g., number of different sourcesbelow a threshold), the quality of the differing sources (e.g., allsources have a 10 reliability rating), and/or any other analysis. Forexample, if the user's sources are the same except for one additionalapproved website, then the user's fact check and the previous fact checkare considered not to be substantially different.

In some embodiments, users receive benefits by fact checking content. Insome embodiments, users register to fact check and/or use their socialnetworking identification for fact checking and receiving benefits. Forexample, a user agrees to fact check a television program for freeaccess to the television program. In another example, a user fact checksa television program and is able to watch the next television programcommercial-free. In another example, a user agrees to fact check aprogram, and is provided the program is streamed to the user for free.Any benefit is able to be provided, including, but not limited to,commercial-free, shortened/fewer commercials, extended content, a period(e.g., month) of free cable/Internet access, program-specific access forfree (e.g., access to News Show X), discounted access (e.g., 50% off),free access to related or unrelated content and/or any other benefit.For example, if the user fact checks News Show X, then they are givenfree access to News Show Y. In another example, if the user fact checksNews Show X, they are given commercial free viewing of the next footballgame of their favorite team. In some embodiments, users are presentedselectable benefits from which to choose. For example, a user is offereda free movie, free sporting event programming or a 50% off download of anew release game, if they fact check News Show X. In some embodiments,the user is required to fact check a certain amount of content and/orreceive an accuracy rating above a threshold to receive the benefits.For example, a user agrees to fact check News Network X's content forfree access to the content. If the user abuses the agreement, and doesnot fact check the content or provides inaccurate fact check results,then the user's access is terminated. If the user provides accurate factcheck results, then the user is able to continue to receive free access.The user is able to fact check the content in any manner. For example,the user is able to manually fact check the content and provide theresults to a central or distributed fact checking system. In anotherexample, the user is able to utilize an automatic fact checkingimplementation that the user has modified (e.g., by selecting sources,monitoring rules, processing rules). In another example, users aregrouped or form groups to fact check content (e.g., crowdsourcing), sothat the groups work together to generate fact check results. Thebenefits are able to be applied to any type of content/services. Forexample, users of a social networking service are able to receiveexpanded access for fact checking, or no advertisement browsing as abenefit for fact checking, and/or any other benefits. In additionalexamples, users who agree to fact check YouTube content or provide aspecified number (e.g., 10) accurate fact check results, are allowed towatch YouTube videos without commercials for a day, or users who factcheck other users' Facebook® pages do not have any advertisementsdisplayed when they browse Facebook® or listen to a music playingservice such as Pandora.

In some embodiments, the social networking fact checking system is asmartphone application including, but not limited to, an iPhone®, Droid®or Blackberry® application. In some embodiments, a broadcaster performsthe fact checking. In some embodiments, a user's television performs thefact checking. In some embodiments, a user's mobile device performs thefact checking and causes (e.g., sends) the results to be displayed onthe user's television and/or another device. In some embodiments, thetelevision sends the fact checking result to a smart phone.

Utilizing the social networking fact checking system, method and devicedepends on the implementation to some extent. In some implementations, atelevision broadcast uses fact checking to fact check what is said orshown to the viewers, and a mobile application, in some embodiments,uses fact checking to ensure a user provides factually correctinformation. Other examples include where web pages or social networkingcontent (e.g., tweet or Facebook® page) are processed, fact checked, anda result is provided. The fact checking is able to be implementedwithout user intervention. For example, if a user is watching a newsprogram, the fact checking is able to automatically occur and presentthe appropriate information. In some embodiments, users are able todisable the fact checking if desired. Similarly, if a user implementsfact checking on his mobile application, the fact checking occursautomatically. For a news company, the fact checking is also able to beimplemented automatically, so that once installed and/or configured, thenews company does not need take any additional steps to utilize the factchecking. In some embodiments, the news company is able to takeadditional steps such as adding sources. In some embodiments, newscompanies are able to disable the fact checking, and in someembodiments, news companies are not able to disable the fact checking toavoid tampering and manipulation of data. In some embodiments, one ormore aspects of the fact checking are performed manually.

In operation, the social networking fact checking system, method anddevice enable information to be fact checked in real-time andautomatically (e.g., without user intervention). The monitoring,processing, fact checking and providing of status are each able to occurautomatically, without user intervention. Results of the fact checkingare able to be presented nearly instantaneously, so that viewers of theinformation are able to be sure they are receiving accurate and truthfulinformation. Additionally, the fact checking is able to clarify meaning,tone, context and/or other elements of a comment to assist a user orviewer. By utilizing the speed and breadth of knowledge that comes withautomatic, computational fact checking, the shortcomings of human factchecking are greatly overcome. With instantaneous or nearlyinstantaneous fact checking, viewers will not be confused as to whatinformation is being fact checked since the results are postedinstantaneously or nearly instantaneously versus when a fact check isperformed by humans and the results are posted minutes later. The rapidfact checking provides a significant advantage over past data analysisimplementations. Any of the steps described herein are able to beimplemented automatically. Any of the steps described herein are able tobe implemented in real-time or non-real-time.

Examples of Implementation Configurations:

Although the monitoring, processing, fact checking and indicating areable to occur on any device and in any configuration, these are somespecific examples of implementation configurations. Monitoring,processing, fact checking and providing all occur on a broadcaster'sdevices (or other emitters of information including, but not limited to,news stations, radio stations and newspapers). Monitoring, processingand fact checking occur on a broadcaster's devices, and providing occurson an end-user's device. Monitoring and processing occur on abroadcaster's devices, fact checking occurs on a broadcaster's devicesin conjunction with third-party devices, and providing occurs on anend-user's device. Monitoring occurs on a broadcaster's devices,processing and providing occur on an end-user's device, and factchecking occurs on third-party devices. Monitoring, processing, factchecking, and providing all occur on third-party devices. Monitoring,processing, fact checking, and providing all occur on an end-user'sdevice. Monitoring, processing and fact checking occur on a socialnetworking site's device, and providing occurs on an end-user's device.These are only some examples; other implementations are possible.Additionally, supplemental information is able to be monitored for,searched for, processed and/or provided using any of the implementationsdescribed herein.

Fact checking includes checking the factual accuracy and/or correctnessof information. The type of fact checking is able to be any form of factchecking such as checking historical correctness/accuracy, geographicalcorrectness/accuracy, mathematical correctness/accuracy, scientificcorrectness/accuracy, literary correctness/accuracy, objectivecorrectness/accuracy, subjective correctness/accuracy, and/or any othercorrectness/accuracy. Another way of viewing fact checking includesdetermining the correctness of a statement of objective reality or anassertion of objective reality. Yet another way of viewing fact checkingincludes determining whether a statement, segment or phrase is true orfalse.

Although some implementations and/or embodiments have been describedrelated to specific implementations and/or embodiments, and someaspects/elements/steps of some implementations and/or embodiments havebeen described related to specific implementations and/or embodiments,any of the aspects/elements/steps, implementations and/or embodimentsare applicable to other aspects/elements/steps, implementations and/orembodiments described herein.

The present invention has been described in terms of specificembodiments incorporating details to facilitate the understanding ofprinciples of construction and operation of the invention. Suchreference herein to specific embodiments and details thereof is notintended to limit the scope of the claims appended hereto. It will bereadily apparent to one skilled in the art that other variousmodifications may be made in the embodiment chosen for illustrationwithout departing from the spirit and scope of the invention as definedby the claims.

What is claimed is:
 1. A method programmed in a non-transitory memory ofa device comprising: a. automatically analyzing social networkinginformation of a user including: i. capturing the social networkinginformation from a social networking system; and ii. parsing the socialnetworking information into parsed segments based on punctuation withinand at an end of sentences within the social networking information; b.detecting bending of a flexible screen of the device by detectingpressure, wherein detecting the bending of the flexible screen of thedevice approves a source as source information; c. automatically factchecking, using the device, the social networking information todetermine a factual accuracy of the social networking information bycomparing the parsed segments of the social networking information withthe source information, wherein the source information comprises onlyapproved social networking information, wherein the approved socialnetworking information includes user-approved social networkinginformation approved by the user and contact-approved social networkinginformation approved by contacts of the user, wherein the approvedsocial networking information approved by the user or the contacts ofthe user comprises visited social networking information visited by theuser or the contacts of the user but not disapproved by the user or thecontacts of the user, wherein the contacts of the user are the contactsof the user in the social networking system, wherein fact checkingincludes determining a text string of the social networking informationis in the source information, wherein the source information containingthe text string of the social networking information is an agreeingsource, further wherein fact checking includes determining a number ofagreeing highest weighted sources and multiplying the number of agreeinghighest weighted sources by a highest weight value, determining thenumber of agreeing second highest weighted sources and multiplying thenumber of agreeing second highest weighted sources by a second highestweight value, and continuing through determining the number of agreeinglowest weighted sources and multiplying the number of agreeing lowestweighted sources by a lowest weight value and combining the multiplyingresults to determine a total value, and upon determining the total valueis above a fact check threshold, the automatic fact checking result istrue, and upon determining the total value is not above the fact checkthreshold, the automatic fact checking result is false; and d.automatically presenting a status of the social networking informationin real-time based on the automatic fact checking result from thecomparison of the social networking information with the sourceinformation.
 2. The method of claim 1 further comprising: determining afirst confidence score of the automatic fact checking result based onthe number of agreeing sources and a second number of disagreeingsources; comparing the first confidence score of the automatic factchecking result with a confidence threshold; fact checking usingcrowdsourced data to generate a crowdsourced result upon determining theautomatic fact checking does not return the automatic fact checkingresult with the first confidence score above the confidence threshold;comparing the first confidence score of the automatic fact checkingresult and a second confidence score of the crowdsourced result; andutilizing the result with a higher confidence score as the status of thesocial networking information.
 3. The method of claim 1 furthercomprising automatically sending the status of the social networkinginformation to contacts of the user, wherein only certain types of factcheck statuses are automatically sent to the contacts, wherein thecertain types are limited to lies and misinformation; and automaticallysending additional information with the status to provide context forthe social networking information, wherein the additional informationincludes a snippet of original content.
 4. The method of claim 1 furthercomprising: approving information as the source information bymicroblogging a link to the information including a hashtag within amicroblog, the hashtag indicating approval or disapproval of theinformation.
 5. The method of claim 1 further comprising: approvinginformation as the approved social networking information by the user orthe contacts of the user visiting the information using a browser butnot disapproving the information; determining the approved socialnetworking information is linked to additional sources with a samereliability rating as the approved social networking information; andautomatically approving the additional sources as the approved socialnetworking information.
 6. The method of claim 1 wherein the approvedsocial networking information approved by the user or the contacts ofthe user comprises the visited social networking information visited bythe user or the contacts of the user while logged in to the socialnetworking system.
 7. The method of claim 1 further comprising:receiving suggested social networking information suggested to the userbased on the contacts of the user and characteristics of the user; andapproving or disapproving the suggested social networking information asthe source information.
 8. The method of claim 1 further comprising:receiving approvals and disapprovals of information as the sourceinformation, wherein the user and the contacts of the user are able toapprove and disapprove the information as the source information; andresolving a conflict as to whether the information is approved ordisapproved by using an approval or disapproval choice of a person, whoapproved or disapproved the information, with a highest validity ratingto determine whether the information is approved or disapproved, whereinthe highest validity rating is based on fact checking results ofcomments by the user and the contacts of the user.
 9. The method ofclaim 8 further comprising: calculating a base validity rating for eachuser; calculating contact validity ratings for contacts of each user;and combining the base validity rating and the contact validity ratingsto generate a final validity rating for each user, wherein the contactvalidity ratings for the contacts are weighted depending on the degreeof separation from the user, wherein the highest validity rating isdetermined from the final validity rating for each user.
 10. The methodof claim 1 further comprising: receiving approvals and disapprovals ofinformation as the source information, wherein the user and the contactsof the user are able to approve and disapprove the information as thesource information; and resolving a conflict as to whether theinformation is approved or disapproved, wherein multiple users approveand disapprove the information, by comparing a first tally of approvalsof the information with a second tally of disapprovals of theinformation, and approving the information upon determining the firsttally is greater than the second tally, and disapproving the informationupon determining the first tally is not greater than the second tally.11. The method of claim 1 further comprising: automatically sharingsources with contacts of the user using social networking immediatelyafter the user approves the sources; and enabling the contacts toapprove or disapprove some or all of the sources shared by the user byselecting approve or disapprove.
 12. The method of claim 1 furthercomprising: automatically determining the user is registering for asecond social networking system; and automatically verifying an identityof the user using fact checking, wherein the social networkinginformation is the identity of the user.
 13. The method of claim 1further comprising: automatically determining the user is attempting toconnect with a second user on the social networking system, wherein thesocial networking information is a user communication to the seconduser; and automatically verifying the user and the second user usingfact checking.
 14. The method of claim 1 further comprising:automatically detecting a same phrase provided by the user and otherusers participating on the social networking system, wherein the socialnetworking information includes the same phrase; and automaticallyconnecting the user and the other users based on the same phrasedetected, wherein the same phrase detected is not factually accurate asdetermined by the fact checking.
 15. The method of claim 12 whereincomparing the social networking information with source informationfurther includes comparing an image from a current video scan of theuser with a past photograph of the user to determine any factualinaccuracies in the current video scan.
 16. The method of claim 14further comprising: storing fact checked social networking informationdetermined to be not factually accurate and a username of the usercorresponding to the fact checked social networking information in adatabase; and matching the fact checked social networking informationamong users.
 17. A method programmed in a non-transitory memory of adevice comprising: a. capturing social networking information of a userfrom a social networking system; b. parsing the social networkinginformation into parsed segments based on punctuation within and at anend of sentences within the social networking information; c. approvingsources for source information by sending a communication with aspecific identifier indicating approval or disapproval of the sources,wherein the user and contacts of the user are able to approve anddisapprove information as the source information; d. adding, to a sourcedata structure containing the source information used for fact checking,an approval or disapproval selection of a contact, who approved ordisapproved the information, with a closest relationship to the userupon determining there is a conflict as to whether the information isapproved or disapproved; e. detecting bending of a flexible screen ofthe device by detecting pressure, wherein detecting the bending of theflexible screen of the device approves a source as the sourceinformation; f. automatically fact checking, using the device, thesocial networking information to determine a factual accuracy of thesocial networking information by comparing the parsed segments of thesocial networking information with the source information in the sourcedata structure to generate an automatic fact checking result, whereinthe source information excludes non-social networking information,wherein fact checking includes determining a text string of the socialnetworking information is in the source information, wherein the sourceinformation containing the text string of the social networkinginformation is an agreeing source, further wherein fact checkingincludes determining a number of agreeing highest weighted sources andmultiplying the number of agreeing highest weighted sources by a highestweight value, determining the number of agreeing second highest weightedsources and multiplying the number of agreeing second highest weightedsources by a second highest weight value, and continuing throughdetermining the number of agreeing lowest weighted sources andmultiplying the number of agreeing lowest weighted sources by a lowestweight value and combining the multiplying results to determine a totalvalue, and upon determining the total value is above a fact checkthreshold, the automatic fact checking result is true and upondetermining the total value is not above the fact check threshold, theautomatic fact checking result is false, wherein users in a socialnetwork are grouped in different levels, and each level affects a weightof sources approved by the users such that the sources of the users in ahigher level have more weight than the sources of the users in a lowerlevel; g. fact checking the social networking information by comparingthe social networking information with crowdsourced data to generate acrowdsourced result; and h. automatically presenting a status of thesocial networking information in real-time based on comparing the socialnetworking information with the source information and the crowdsourceddata, wherein the status is based on comparing a first confidence scoreof the automatic fact checking result and a second confidence score ofthe crowdsourced result, and selecting the result with the higherconfidence score, further wherein at least one of the first confidencescore of the automatic fact checking result and the second confidencescore of the crowdsourced result is presented with the status of thesocial networking information.
 18. A device comprising: a. a flexiblescreen configured for detecting bending of the flexible screen based onpressure, wherein detecting the pressure on the flexible screen approvesa source as the source information; b. a non-transitory memory forstoring an application for automatically performing the following steps:i. processing content based on detecting the touch of the touchscreendisplay, wherein the content comprises social networking information ofa user; ii. fact checking the social networking information to determinea factual accuracy of the social networking information by comparing thesocial networking information with the source information to generate anautomatic fact checking result, wherein fact checking includesdetermining a text string of the social networking information is in thesource information, wherein the source information containing the textstring of the social networking information is an agreeing source,further wherein fact checking includes determining a number of agreeinghighest weighted sources and multiplying the number of agreeing highestweighted sources by a highest weight value, determining the number ofagreeing second highest weighted sources and multiplying the number ofagreeing second highest weighted sources by a second highest weightvalue, and continuing through determining the number of agreeing lowestweighted sources and multiplying the number of agreeing lowest weightedsources by a lowest weight value and combining the multiplying resultsto determine a total value, and upon determining the total value isabove a fact check threshold, the automatic fact checking result is trueand upon determining the total value is not above the fact checkthreshold, the automatic fact checking result is false, wherein thesource information excludes non-social networking information, whereinthe source information comprises only approved social networkinginformation approved by the user or contacts of the user, wherein thecontacts of the user are the contacts of the user in a social networkingsystem, wherein the approved social networking information approved bythe user or the contacts of the user comprises visited social networkinginformation visited by the user or the contacts of the user but notdisapproved by the user or the contacts of the user, wherein theapproved social networking information approved by the user or thecontacts of the user comprises the visited social networking informationvisited by the user or the contacts of the user while logged in to thesocial networking system, wherein the approved social networkinginformation approved by the user comprises suggested social networkinginformation suggested to the user based on the contacts of the user andcharacteristics of the user, wherein the user and the contacts of theuser are able to approve and disapprove information as sourceinformation, and if there is a conflict as to whether the information isapproved or disapproved, and multiple users approve and disapprove theinformation, then the higher of the number of approvals versusdisapprovals determines if the information is approved or disapproved,wherein sources are automatically shared with contacts using socialnetworking after the user accepts the sources to enable the contacts toaccept or reject some or all of the sources; iii. fact checking thesocial network information using crowdsourced data to generate acrowdsourced result; iv. comparing confidence scores of the automaticfact checking result and the crowdsourced result, and the result with ahigher confidence score is used to generate the status of the socialnetworking information; v. presenting a status of the social networkinginformation in real-time; and vi. sending the status of the socialnetworking information to the contacts of the user, wherein only certaintypes of fact check statuses are automatically sent to the contacts,wherein the certain types are limited to lies and misinformation stored,classified and retrieved from a look-up table, further whereinadditional information is sent with the status to provide context forthe social networking information, wherein the additional informationincludes a snippet of original content; and c. a processor forprocessing the application.
 19. The device of claim 18 wherein theapplication is further for automatically performing: comparing thestatus of the social networking information based on the fact checkingfor the user with a second status of the social networking informationbased on fact checking for the contacts of the user; presenting thesecond status of the social networking information based on the factchecking for the contacts of the user upon determining the status of thesocial networking information and the second status of the socialnetworking information do not match; and presenting a quantity ofcontacts who received the second status of the social networkinginformation.
 20. The device of claim 18 wherein the touchscreen displayis configured for displaying a list of segments based on priority to befact checked and receiving a selection by the user of one or more of thesegments, and the application for fact checking the one or more selectedsegments.